Chip surface defect detection method and device

According to the chip surface defect detection method and equipment provided by the embodiment of the invention, through an automatic mode, the time and cost of manual detection are greatly reduced, and the production efficiency is greatly improved. Compared with traditional manual or semi-automatic...

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Main Author CHEN BINGGUI
Format Patent
LanguageChinese
English
Published 19.03.2024
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Abstract According to the chip surface defect detection method and equipment provided by the embodiment of the invention, through an automatic mode, the time and cost of manual detection are greatly reduced, and the production efficiency is greatly improved. Compared with traditional manual or semi-automatic detection, the technical scheme utilizes the deep learning model to carry out defect detection, so that the defects on the surface of the microelectronic chip can be identified and positioned more accurately, and the product quality is improved. Through a feedback correction mechanism, model parameters can be continuously optimized and adjusted, so that the model has good adaptability and robustness when facing new and unknown defect types. 本申请实施例提供的芯片表面缺陷检测方法及设备,通过自动化的方式,大幅减少了人工检测的时间和成本,极大地提高了生产效率。与传统的手动或半自动化检测相比,该技术方案利用深度学习模型进行缺陷检测,能够更准确地识别和定位微电子芯片表面的缺陷,从而提高产品质量。通过反馈修正机制,可以不断优化和调整模型参数,使得模型在面对新的、未知的缺陷类型时也能有良好的适应性和鲁棒性。
AbstractList According to the chip surface defect detection method and equipment provided by the embodiment of the invention, through an automatic mode, the time and cost of manual detection are greatly reduced, and the production efficiency is greatly improved. Compared with traditional manual or semi-automatic detection, the technical scheme utilizes the deep learning model to carry out defect detection, so that the defects on the surface of the microelectronic chip can be identified and positioned more accurately, and the product quality is improved. Through a feedback correction mechanism, model parameters can be continuously optimized and adjusted, so that the model has good adaptability and robustness when facing new and unknown defect types. 本申请实施例提供的芯片表面缺陷检测方法及设备,通过自动化的方式,大幅减少了人工检测的时间和成本,极大地提高了生产效率。与传统的手动或半自动化检测相比,该技术方案利用深度学习模型进行缺陷检测,能够更准确地识别和定位微电子芯片表面的缺陷,从而提高产品质量。通过反馈修正机制,可以不断优化和调整模型参数,使得模型在面对新的、未知的缺陷类型时也能有良好的适应性和鲁棒性。
Author CHEN BINGGUI
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Title Chip surface defect detection method and device
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